dataframe find nan rows
df[df.isnull().any(axis=1)]
dataframe find nan rows
df[df.isnull().any(axis=1)]
count nan pandas
#Python, pandas
#Count missing values for each column of the dataframe df
df.isnull().sum()
count rows with nan pandas
np.count_nonzero(df.isnull().values)
np.count_nonzero(df.isnull()) # also works
number of columns with no missing values
null_cols = df.columns[df.isnull().all()]
df.drop(null_cols, axis = 1, inplace = True)
pandas count number missing values
dfObj.isnull().sum()
pandas count number missing values
dfObj.isnull().sum().sum()
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